Category: Data Science

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. There is a phrase in baseball about pitchers “pitching through pain” that refers to pitchers taking the mound to pitch even though they have aches and pains – sore arms, stiff joints, blisters, strained muscles, etc. The idea is that these pitchers are so tough that they can pitch effectively even though they are not quite physically right. However, when the human system is asked to do something that it’s not prepared to do in the most effective manner, other bad habits emerge in an attempt to counter these ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: saurabh ajmera. As per Wikipedia, Price Elasticity of Demand (PED or ED or PE) is a measure used in economics to show the responsiveness, or change, of the quantity demanded of a good or service to a change in its price when nothing but the price changes. In more precise business terms, it helps in finding those products which have their sales more/less susceptible to price changes. As we know, the demand is inversely proportional to price, it is quite imperative to know this information for optimising sales and margins. Without ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Racheal Chapman. How secure is your data? What measures do you take to hide your confidential data? Can you confidently say that data breaching stands nowhere close to your security? Data breaching is not new and neither will it disappear. As technology rises with new developments, hackers are studying the tools closely to understand how they can grasp your sensitive information? In 2019, one of the articles stated, ‘’61% of IT professionals have experienced a serious data breach’’. Imagine when the experts get hit with such a crucial issue, do you ... Read More

Feed: R-bloggers. Author: Thinking inside the box. [This article was first published on Thinking inside the box , and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. A new package of mine arrived on CRAN yesterday, having been uploaded a few days prior on the weekend. It extends the most excellent (and very minimal / zero depends) unit testing package tinytest by Mark van der Loo with the very clever and well-done diffobj package ... Read More

Feed: R-bloggers. Author: Chris Paciorek. [This article was first published on R – NIMBLE, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. We’ll be giving a short course on NIMBLE on January 7, 2020 at the Bayes Comp 2020 conference being held January 7-10 in Gainesville, Florida, USA. Bayes Comp is a popular biennial ISBA-sponsored conference focused on computational methods/algorithms/technologies for Bayesian inference. The short course focuses on programming algorithms in NIMBLE and ... Read More

Feed: R-bloggers. Author: LeaRning Stats. [This article was first published on LeaRning Stats, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Chebychev’s Theorem gives bounds on how spread out a probability distribution can be from the mean, in terms of the standard deviation. More precisely, if (X) is a random variable with mean (mu) and standard deviation (sigma), then [P(|X – mu| ge k sigma) le frac {1}{k^2}.] When I was an undergraduate ... Read More

Feed: R-bloggers. Author: Random R Ramblings. [This article was first published on Random R Ramblings, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Related If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. I have been looking at this problem over a few years now The IoT industry often speaks of handling both high volumes and high throughputs of data However, currently, I find that there are not many use cases for IoT streaming analytics which are unique The 'unique' and 'currently' bits are important i.e. identifying use cases that need the analytics primarily implemented in the stream (and not applied to data when at rest) Do you know of companies/ vendors actually implementing this? (in production today) On one hard, every ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link. Announcements Migrating R Applications to the Cloud - Upcoming Webinar Learn a new skill at #StrataData New York. Featured Resources and Technical Contributions 10 Visualizations Every Data Scientist Should Know Calculating Price Elasticity Through KNIME Stratified vs Cluster vs Quota Sampling The First Article About Theoretical Data Science (and easy to read) Introduction to Various Reinforcement Learning Algorithms Linear ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Stephanie Glen. What is the Difference Between Stratified Sampling and Cluster Sampling? The main difference between stratified sampling and cluster sampling is that with cluster sampling, you have natural groups separating your population. For example, you might be able to divide your data into natural groupings like city blocks, voting districts or school districts. With stratified random sampling, these breaks may not exist*, so you divide your target population into groups (more formally called "strata"). In stratified sampling, a sample is drawn from each strata (using a random sampling method like simple ... Read More